Software Carpentry's mission is to help scientists and engineers become more productive by teaching them basic lab skills for computing like program design, version control, data management, and task automation. This two-day hands-on bootcamp will cover basic concepts and tools; participants will be encouraged to help one another and to apply what they have learned to their own research problems.
Instructors: Bernhard Konrad, Scott Chamberlain, Christina Koch, Lynne Williams
Who: The course is aimed at postgraduate students and other scientists who are familiar with basic programming concepts (like loops, conditionals, arrays, and functions) but need help to translate this knowledge into practical tools to help them work more productively.
Where: Simon Fraser University Burnaby campus. Map here. The room for the R event on Day 2 (notice the room change) is ASB 9896 E in the Applied Sciences Building, and for Python is K9509 in Shrum Kinesiology. You can look at this map on the Simon Fraser University website to find the building that you need to go to.
Requirements: Participants must bring a laptop with a few specific software packages installed (listed below).
Contact: Please mail admin@software-carpentry.org for more information.
Room | SCK 9509 | TASC-I 9204 E |
---|---|---|
8:30 - 9:00 | Setup help | Setup help |
9:00 - 9:15 | Overview and introduction (Christina) | Overview and introduction (Bernhard) |
9:15 - 10:30 | Navigating in the shell (Lynne) | Intro to R and RStudio (Bernhard) |
10:50 - 12:00 | Local version control (Christina) | Care and feeding of R objects (Scott) |
12:00 - 1:00 | Lunch break (no lunch provided) | Lunch break (no lunch provided) |
1:00 - 2:30 | Intro to remote version control + shell scripts and automation (Christina and Lynne) | Local version control (Bernhard) |
2:50 - 4:30 | Introduction to python, and ipython blocks (Lynne) | Data aggregation using plyr (Scott) |
Room | SCK 9509 | ASB 9896 E |
---|---|---|
9:00 - 10:00 | Day 1 review, more shell, Python intro (Lynne) | Day 1 review. Project organization (Bernhard) Overview of knitr, RPubs (Scott) |
10:20 - 12:00 | Python flow control, functions, plotting (Lynne) | Version control in shell and Github (Bernhard) |
12:00 - 1:00 | Lunch break (no lunch provided) | Lunch break (no lunch provided) |
1:00 - 2:30 | Resolving conflicts (git) and fixing bugs (python) (Christina) | Making figures using ggplot2 (Scott) |
2:50 - 4:30 | Python from the command line (Christina) | Functions and debugging (Bernhard) The R workflow in action (Scott) |
To participate in a Software Carpentry bootcamp, you will need working copies of the software described below. Please make sure to install everything (or at least to download the installers) before the start of your bootcamp.
When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on Mac OS X and Linux is usually set to Vim, which is not famous for being intuitive. If you accidentally find yourself stuck in it, type the escape key, followed by ':q!' (colon, lower-case 'q', exclamation mark) to return to the shell.
Bash is a commonly-used shell. Using a shell gives you more power to do more tasks more quickly with your computer.
Git is a state-of-the-art version control system. It lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com.
Depending on the programming language that you signed up for you need to install Python or R, but not both.
Python is becoming very popular in scientific computing,
and it's a great language for teaching general programming concepts due to its easy-to-read syntax.
We teach with Python version 2.7,
since it is still the most widely used.
Installing all the scientific packages for Python individually can be a bit difficult,
so we recommend an all-in-one installer.
Depending on the programming language that you signed up for you need to install Python or R, but not both.
R is a programming language that specializes in statistical
computing. It is a powerful tool for exploratory data analysis. To
interact with R, we will
use RStudio, an interactive
development environment (IDE).
For an all-in-one installer:
Notepad++ is a popular free code editor for Windows. Be aware that you must add its installation directory to your system path in order to launch it from the command line (or have other tools like Git launch it for you). Please ask your instructor to help you do this. If you are in the R section, RStudio will be sufficient.
Install Git for Windows by download and running the installer This will provide you with both Git and Bash in the Git Bash program.
Please follow our R install instructions.
The default shell in all versions of Mac OS X is bash,
so no need to install anything. You access bash from
the Terminal (found
in /Applications/Utilities
). You may want
to keep Terminal in your dock for this workshop.
We recommend
Text Wrangler or
Sublime Text.
In a pinch, you can use nano
,
which should be pre-installed.
If you are in the R section, RStudio will be sufficient.
Installing Git may require you to first install XCode. This is a very large download (several gigabytes), so please do it before arriving at the bootcamp.
Go to the Xcode website. Get XCode from the App Store making certain to install the command line tools (from the Download preferences pane). Git is included in the command line tools.
If you have Mac OS X 10.6,
first get XCode by going to
the Apple developer site.
You have to sign in with an Apple ID linked to a Developer account.
If you don't have one,
you can register and create one.
Once you log in,
go to page 8 and find "XCode 3.2.6 and iOS SDK 4.3 for Snow Leopard".
Click to open that section,
and then download the .dmg
file.
Finally,
install just git.
We recommend the all-in-one scientific Python installer Anaconda. (Installation requires using the shell and if you aren't comfortable doing the installation yourself just download the installer and we'll help you at the bootcamp.)
bash Anaconda-and then press tab. The name of the file you just downloaded should appear.
yes
and press enter to approve
the license. Press enter to approve the default
location for the files. Type yes
and
press enter to prepend Anaconda to
your PATH
(this makes the Anaconda
distribution the default Python).
Please follow our R install instructions.
The default shell is usually bash
,
but if your machine is set up differently
you can run it by opening a terminal and typing bash
.
There is no need to install anything.
If Git is not already available on your machine you can try
to install it via your distro's package manager
(e.g. apt-get
).
Kate is one option for Linux users.
In a pinch, you can use nano
,
which should be pre-installed.
If you are in the R section, RStudio will be sufficient.
Please follow our R install instructions.
We recommend the all-in-one scientific Python installer Anaconda. (Installation requires using the shell and if you aren't comfortable doing the installation yourself just download the installer and we'll help you at the boot camp.)
bash Anaconda-and then press tab. The name of the file you just downloaded should appear.
yes
and press enter to approve
the license. Press enter to approve the default
location for the files. Type yes
and
press enter to prepend Anaconda to
your PATH
(this makes the Anaconda
distribution the default Python).